[Text on screen] Hyperconnected AI Era. Are you Agile or Antiquated?
[Sam Bednall, Telstra International speaking] The industry has now entered what Telstra is defining as the hyperconnected digital business and AI era.
This era is characterized by a landscape of distributed workforces, decentralized applications, external vertical ecosystems, and the proliferation of machine-to-machine and human-to-machine digital interactions.
In 2024 and beyond, companies will initially explore and then widely adopt AI technologies and platforms. Having a well-architected underlying infrastructure that facilitates an organization's ability to create, connect, contextualize, and consume data in real-time is essential to driving competitive advantage in this era.
[Text on screen] Leveraging Generative AI
Telstra commissioned a global report on generative AI. This report offers a number of compelling insights. For instance, a significant majority of respondents believe they will successfully leverage generative AI to become disruptors in their industry over the next five years. However, the report also identified that fewer than 30% of respondents rank their current IT environment as being conducive to the rapid adoption of generative AI.
[Text on screen] 19% volume of data available for large language models.
[Text on screen] 13% data storage infrastructure.
[Text on screen] 7% suitability of existing in-house or outsourced computing platforms.
Specifically and notably, only 19% of respondents currently believe they have sufficient volume of data favorable to the rapid adoption of generative AI. More strikingly, only 13% and 7% respectively indicated that they have the necessary data storage, infrastructure, and computing platforms for their AI adoption requirements.
Put another way, the respondents recognize that company-specific and domain-specific AI will drive business value, but they will only achieve competitive business advantage with the prerequisite IT infrastructure.
[Text on screen] Hyperconnected Digital Infrastructure.
AI models, along with their training methods, ingest vast quantities of data for learning and adaptation purposes. For the majority of businesses, data is originating from various sources, including omni-channel customer experiences, supply chain ecosystems, employees, business processes and so forth. Furthermore, the proliferation of investments in machine-to-machine and human-to-machine digital interactions also generates substantial new data, which businesses must now also manage.
In the hyperconnected AI era, the concept of data gravity has become a critical consideration. Data gravity is not a new term. It relates to the tendency for data to attract additional business logic and applications, similar to the way a mass attracts objects through gravitational pull. The notion of data gravity has increased in importance, because as data grows in size and complexity, it becomes more difficult and resource-intensive to move. Consequently, applications and services are more likely to be deployed closer to where the data resides, perhaps to reduce latency, minimize transfer costs, or improve performance and user experiences.
Telstra advises organizations to embark upon a hyperconnected digital infrastructure strategy. What I mean by that is we will work with our customers to help them understand the critical importance of a right-fit, right-size, and right-locate approach to their data and AI deployments.
Right-fit focuses on determining the most suitable technology stack to run your AI applications and underlying data estate. Many organizations will need to radically simplify their data architecture to maximize their business outcomes. Using Telstra as an example, we are currently reducing our data estate platforms from 50 to 5 to better support our AI objectives.
Right-sizing matches resources to workloads, making sure you are running your digital infrastructure in the most effective manner possible. For example, hyperscaler consumption models can be suitable for many applications, but IT leaders now need to consider the scale of data as well as the volume of computations that AI workloads will demand.
Finally, right-locate focuses on ensuring your applications and data reside in IT environments that are most suited for the workload and business requirements. For modern AI-enabled workloads, weighing up considerations of latency sensitivity, data sovereignty, and compute and storage economies of scale can be highly complex.
In today's hyperconnected business and AI era, IT leaders are being challenged to redefine their strategy to better support AI-enabled workloads and technologies.
So where are you on your journey of hyperconnected digital infrastructure? Do you aspire for an AI-enabled agile infrastructure or do you risk having antiquated environments?
[Text on screen] www.telstrainternational.com/GenAI
